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ROOT_DIR=/opt/jupyter_gpu/pytorch
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DATA_DIR=/opt/jupyter_gpu/data
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JUPYTER_PORT=8888
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PUID=1000
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PGID=1000
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# -------------------------------------------------------
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# Relies on JUPYTER_PORT being set in docker-compose.yml
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# -------------------------------------------------------
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FROM pytorch/pytorch:latest
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# Install packages
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RUN pip install jupyterlab ipywidgets
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RUN pip install pandas numpy
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RUN pip install plotly
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RUN pip install seaborn
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RUN pip install statsmodels
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#
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RUN pip install autogluon
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#
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RUN pip install scikit-learn
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RUN pip install Arch
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RUN pip install Quantlib
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RUN pip install Backtrader
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RUN pip install pyfolio
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RUN pip install XGBoost
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# Install additional applications
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RUN apt update
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RUN apt-get install graphviz -y
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RUN mkdir -p /workspace
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# Set environment variables, etc.
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#ENV MY_ENV_VAR=myvalue
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COPY cvttpy /cvttpy
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# Set the working directory
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WORKDIR /workspace
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# Expose the port for JupyterLab
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EXPOSE ${JUPYTER_PORT}
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# Command to run JupyterLab
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CMD ["jupyter-lab", "--ip=0.0.0.0", "--port=8888", "--no-browser", "--allow-root", "--NotebookApp.token=''"]
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version: '3.8'
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#==================================================
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# Relies on the file `.env` content for varables:
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# ROOT_DIR
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# DATA_DIR
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# JUPYTER_PORT
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# UID
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# GID
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#==================================================
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services:
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jupyter:
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# user: "${UID}:${GID}"
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# build: ${ROOT_DIR}
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image: cloud21.cvtt.vpn:5500/jupyter_gpu_pt:latest
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container_name: jupyter_gpu_pt
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runtime: nvidia
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restart: unless-stopped
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environment:
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- JUPYTER_ENABLE_LAB=yes
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- PYTHONPATH=/cvtt/prod
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volumes:
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- ${ROOT_DIR}/notebooks:/workspace
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- ${ROOT_DIR}/jupyter_settings/user-settings:/root/.jupyter/lab/user-settings
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- ${ROOT_DIR}/jupyter_settings/workspaces:/root/.jupyter/lab/workspaces
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- ${ROOT_DIR}/.cache/torch:/root/.cache/torch
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- ${DATA_DIR}:/workspace/data
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ports:
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- "${JUPYTER_PORT}:${JUPYTER_PORT}"
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shm_size: "8gb"
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@@ -0,0 +1,3 @@
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ROOT_DIR=/opt/jupyter_gpu/tensorflow
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DATA_DIR=/opt/jupyter_gpu/data
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JUPYTER_PORT=9999
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@@ -0,0 +1,42 @@
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# Use the official TensorFlow image with GPU support
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FROM tensorflow/tensorflow:latest-gpu-jupyter
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# Install necessary packages
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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curl \
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ca-certificates \
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graphviz \
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&& rm -rf /var/lib/apt/lists/*
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# RUN useradd -m -s /bin/bash oleg
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RUN mkdir -p /workspace/tf_cache
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# Install packages
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RUN pip install jupyterlab
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RUN pip install pandas
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RUN pip install numpy
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RUN pip install plotly
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RUN pip install seaborn
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RUN pip install statsmodels
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RUN pip install scikit-learn
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RUN pip install Arch
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RUN pip install Quantlib
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RUN pip install Backtrader
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RUN pip install pyfolio
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RUN pip install XGBoost
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# Install additional applications
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# RUN apt update
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# RUN apt-get install graphviz -y
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# Set the working directory
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WORKDIR /workspace
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# Expose the port for JupyterLab
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EXPOSE ${JUPYTER_PORT}
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# Command to run JupyterLab
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CMD ["sh", "-c", "jupyter lab --ip=0.0.0.0 --port=9999 --allow-root --no-browser --NotebookApp.token=''"]
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@@ -0,0 +1,27 @@
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version: '3.8'
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#==================================================
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# Relies on the file `.env` content for varables:
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# ROOT_DIR
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# DATA_DIR
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# JUPYTER_PORT
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#==================================================
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services:
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jupyter:
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image: cloud21.cvtt.vpn:5500/jupyter_gpu_tensorflow:latest
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container_name: jupyter_gpu_tf
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runtime: nvidia
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restart: unless-stopped
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environment:
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- JUPYTER_ENABLE_LAB=yes
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#- PYTHONPATH=/cvtt/prod
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- TF_CACHE_DIR=/workspace/tf_cache
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volumes:
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- ${ROOT_DIR}/notebooks:/workspace
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- ${ROOT_DIR}/jupyter_settings/user-settings:/home/oleg/.jupyter/lab/user-settings
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- ${ROOT_DIR}/jupyter_settings/workspaces:/home/oleg/.jupyter/lab/workspaces
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# - ${DATA_DIR}:/workspace/data
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ports:
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- "${JUPYTER_PORT}:${JUPYTER_PORT}"
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shm_size: "8gb"
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